Back in the 1987 movie Wall Street, Michael Douglas’ character, Gordon Gekko, gave his (in)famous “Greed is Good” speech. The thrust of it all was that greed, “greed for life, for money, for love, for knowledge…has marked the upward surge of mankind.”

The merits of that statement have been argued since Douglas first uttered it and I am not here to defend one side over the other. My point in this article is to relate how greed in excess, greed as theprime motivator in a trader can lead to defeat. The ultimate defeat being blowing up their trading account.

Confession Time: Just so you know that I have had up close and personal run ins with greed, allow me to relate a story. Very early in my trading career, I made a classic rookie blunder. I put on a trade (way too big), seconds after NFP (way too volatile), wanting to make 20 pips on the GBPUSD. If this trade worked out, I thought, it would make my trading week! What a genius idea and what a genius I was to think of it!! Well, the trade made it to +17 pips and stalled. But, guided by greed, I held out for 20 pips (way too stubborn). End result – I lost 23 pips (way too stupid). Lesson on greed learned the hard and expensive way.

Here are two quotes on the emotion of greed from traders that I have worked with…

“Greed has cost me more than anything else.”

“How can I control greed??? That has been my number one problem in trading.”

So how do we, mere mortals that we are, go about controlling this all too human emotion of greed?

First of all, if you can identify at all with these quotes, it means you are aware that greed is negatively impacting your trading and that recognition is a BIG step toward resolving the issue.

Stop being greedy

To keep this detrimental emotion in check, having a definite trading plan written out will go a long way toward eliminating the problem. Keep the plan nearby where you can reference it prior to placing any trade. The plan will be a strategy that you have tested and one that has put pips into your account over time. By this I do not mean positive pips on every single trade since every trade will not be a winner. But, overall, the strategy has been adding to your account size.

Now that we have the trading plan nailed down, we must – MUST – only take trades that fit that plan precisely. If the trade does not measure up, we don’t take the trade – simple as that. We only want to take higher probability trades that are based on our pre-determined plan. This will eliminate randomly jumping into trades based on emotion because “it kind of looks OK”, or the “I just like to be in a trade” syndrome.

Money Management

Never put more than an absolute maximum of 5% of your trading account at risk at any one time. This means no matter how many trades you have open at once, if they ALL turn out to be losers (yes, that can happen), you will not lose more than 5% of your trading account. Keep in mind that when it comes to risk, less is better than more. So 3% risk is better than 5% and 1% is better than 3%…you get the idea.

Also, always trade with a 1:2 Risk Reward Ratio in place. This means if you’re risking 50 pips on a trade you should be looking for at least 100 pips of profit on that trade.

(Later articles and commentaries will specifically and in detail address the concept of Money Management in trading.)

Lastly, once the trade has triggered with stops and limits in place – I cannot emphasize this next point enough – LEAVE IT ALONE!! Just let the trade play itself out according to the original parameters you put into place prior to being in the trade…when emotions were non-existent.

Take a minute and let this sink in…

When you were looking at the charts, checking for trends, support and resistance levels, relevant fundamental announcements and the like, you were totally without emotion. You had no “skin in the game” at that point. The plans that were put together at that time were based on facts. Once the trade is entered , however, emotions can shift into high gear as money – your money – is on the line. Making changes to a fact based, emotionless trading plan based on moment to moment emotional shifts induced by price action in the market is not a prudent way to trade. It is a deadly way to trade.

Managing and dealing with the emotion of greed is not something that will be resolved over the next couple of trades. However, by being conscious of how greed can negatively impact your trading and implementing the former ideas as part of your trading regimen, you will be taking positive steps toward the goal of greed free trading.

I have heard about strategies that invest with multiple trend following funds and allocate capital between them inverse to performance. These strategies will pull money out of funds that have performed well over a period of time and reallocate that money to funds that have underperformed during that time.

The idea behind this type of strategy is that trend followers that have been performing well are due for a correction and funds that have been performing poorly are likely to be coming out of a correction. This allows an investor to have a larger portion of capital invested when a fund logs its biggest gains.

The strategy of doubling down on yourself sounds great in theory, but it also has some major flaws.

A recent post from Dorsey Write Money Management explored a similar concept that allows traders to double down on their own strategy. The post covers an article by Craig Israelsen that that suggests contributing additional funds to your account after losing periods to maintain a minimum overall return.

How Israelsen’s Strategy Works

What Israelsen proposes is geared towards long term investors. He suggests choosing a benchmark number like 8% that an investor will target as an annual return.

During any years where an investor falls short of the 8% return, they should contribute enough funds to make up the difference. However, if the account returns more than 8% they are not obligated to contribute anything further.

This type of strategy will create a smooth equity curve that always moves higher. It takes advantage of the power of dollar cost averaging on the downside, and then lets the upside take care of itself.

Applying The Strategy To Forex

While this strategy is interesting in theory, most Forex traders don’t think in terms of annual return. They are looking to book profits on a daily basis. How could we adjust the strategy to fit that model?

The simple answer would be to set a daily benchmark for the return instead of using an annual return. If your goal is to make a certain amount of money everyday, force yourself to contribute the difference if you come up short.

This would ensure a consistently positive equity curve, so the account value would never erode. However, there are also some drawbacks to this strategy.

Problems with the Strategy

The most obvious issue with this type of strategy is that it assumes that you can afford to contribute enough capital on a regular basis to make up for any losses incurred by your trading. If, at any point, you are unable to enough capital to cover the losses, then the whole strategy falls apart.

Furthering that thought, if you have enough capital coming in to make up for losses in your trading, then why aren’t you investing that capital in your trading in the first place? Why wait until you are losing before investing it? Are you spending that capital foolishly during profitable periods?

While Israelsen’s idea sounds very interesting from a theoretical perspective, it may not be very helpful in actual trading.

Pyramiding in and out of trades is a very popular method used by many traders attempting to maximize profit while limiting losses. However, as with any generally accepted methodology, there is actually more to pyramiding than meets the eye.

There are many instances where pyramiding in or out of positions can actually reduce the overall return or increase the maximum drawdowns of a strategy. Knowing how to isolate and test each aspect of your pyramiding approach can shed a great deal of light on whether it is actually helping your strategy. Sometimes the benefits only exist in our heads.

Pyramiding in and out of positions is generally believed to be a good idea, but Mike shows that in some instances it can be ineffective.

Mike Bryant published a very insightful piece at System Trader Success that took a look at the different aspects of testing an exit strategy that scales out in two steps. The shocking part of the article is that Mike discovered that the system actually performed best when one aspect of the exit strategy was completely eliminated.

The Basic Strategy

The strategy that Mike uses for his article is designed to trade 15 minute bars on the short side of the mini Russell 2000 futures. His strategy establishes a full short position when it receives a signal and then exits half of the position based on one set of circumstances and the other half of the position under another set of circumstances.

When Mike’s strategy takes a new short position, it immediately sets an initial stop and a profit target. If the profit target is hit, the strategy takes a profit on half of the position. The other half of the position adjusts its initial stop to the breakeven point and uses a trailing stop to secure any additional profits.

This strategy represents the basic concept of taking a portion of the profits off the table and leaving the rest of them to run. This is generally accepted as a good idea, but Mike discovered that it was actually hurting the system’s overall performance.

Testing Multiple Exits

In order to test the impact that each of the exits had on the overall strategy, Mike programmed them as two separate strategies and tested them as a combined system. Each of the strategies was programmed to take half a position on each entry and then follow its specific exit criteria.

Using a program that allowed him to optimize how much of the total position should be allocated to each exit strategy, Mike found out that the best overall system would allocate 100% of its capital to the system that based its exits on the trailing stop. Therefore, taking half the position off of the table at a certain profit level was counter-productive in the long-run.

Mike specified in his optimization program that he needed to keep the maximum drawdown under 30%. Using that as a maximum, the combined system returned a net profit of $82,000 on his backtesting data. Maintaining the same maximum drawdown and allocating the entire exit capital to the trailing stop version produced a net profit of $129,000.

Of course, this doesn’t mean that pyramiding is always a bad idea. This is just one strategy that is focused on one specific market and time frame. The important concept is that we must find a way to test all of our assumptions.

The famous MIT Blackjack Team based their systematic approach to blackjack on the idea that they wanted to risk significantly more capital in situations where they had a quantifiable edge. We can use a similar strategy to put more of our capital to work in high probability situations, and we don’t have to worry about getting thrown out of the casino.

The MIT Blackjack Team had players that would place table minimum bets for hours waiting for a deck to become advantageous for the players. When that occurred, they would signal a teammate to join the table and bet the maximum. This allowed them to risk as much money as possible under conditions where they knew they had an edge, without alerting the casinos to their strategy.

We can use a common blackjack strategy to increase our position size in situations where the probability of success is better.

In a recent post on Trader Edge, Brian Johnson explained a quantitative trading strategy that is very similar to what the MIT Blackjack Team was known for. Brian suggests that traders should use a filter to identify the trades with the biggest edge for the trader. This filter will produce very few trades, so it won’t be a tradeable strategy itself, but it can be used to identify the most potentially profitable trades.

Brian’s Filter Example

The example that Brian uses to illustrate his concept is a basic strategy that buys securities that are experiencing short-term pullbacks during long-term uptrends. While he doesn’t give the specifics of this strategy, he does tell us that it produced 790 trades with a profit factor of 3.78 during his backtesting period.

Brian explains that adding a Stochastic filter to his strategy has a varying effect on its performance depending on what value is used for the filter. He produces a chart that shows that using any value between 60 and 100 for the filter has zero effect on the strategy. However, as the value of the Stochastic filter is lowered from 60, it begins to impact the strategy by increasing the profit factor and lowering the number of trade signals.

Brian finds that the sweet spot for his Stochastic filter appears to be a value of 20, which produces a profit factor of 7.77 on 324 trades. He explains that this is where most traders force themselves to make a difficult decision.

Filter or No Filter? Both!

Brian now has two strategies. The strategy with no filter makes less return on a per trade basis, but signals many more trades. On the other hand, his filtered strategy makes far more profit per trade, but generates fewer signals.

What he suggests is the same idea that the MIT Blackjack Team would utilize: Trade both strategies! His simple, but brilliant concept is to take all of the trades that the unfiltered system produces and increase his position size on the trades that meet the criteria of his Stochastic filter. This will allow him to risk more capital in higher probability situations, and less capital in lower-probability situations.

This concept could be applied to almost any trading strategy and filter combination with proper backtesting. Brian makes a point to remind us that we should be cautious not to increase position size past an acceptable overall risk.

Strategies that can demonstrate huge winning percentages through unbiased backtesting are extremely appealing. Imaging the streaks that you could run up if your system was winning on better than 80% of its trades!

Of course we all know that these types of strategies are almost always accompanied by the same tragic flaw: potential for catastrophic losses. That flaw makes these types of strategies great for video games and practice accounts, but not for trading our hard-earned capital. There is no reset button when you are trading real money.

Many high win percentage strategies are described as “picking up pennies in front of a steamroller” because of their potential for severe losses.

These types of strategies are often referred to as “picking up pennies in front of a steamroller,” which provides a vivid mental image of the potential pitfalls. In a recent post, Dan from Theta Trend thought it would be an interesting case study to see how one of these “steamroller” strategies would have fared over the course of 2013.

Dan’s Accelerated pTheta Strategy

The strategy that Dan tested was a version of his pTheta strategy. Here is how he describes it:

The penny system sells out of the money vertical spreads in the $SPX every week using 10 delta weekly options with 8 days to expiration. Every Thursday the system sells a vertical spread.

If the market is closed on a Thursday (Thanksgiving), the strategy sells the verticle spread on the next day. Dan explains that his strategy uses the Parabolic SAR indicator as a trend filter to determine the direction of his trade:

If price is trading above the daily pSAR, the system sells put spreads below the market and call spreads are sold if price is trading below.

This gives us the basic outline of a simple options strategy that makes one trade every single weekwith a very high winning percentage.

Backtesting Dan’s Strategy

Over the course of 2013, Dan’s Accelerated pTheta Strategy would have made a total of 52 trade. Of those trades, 44 would have been profitable and 8 would have been losers. That works out to a win rate of 84.62%. 33 of the trades were on the long side, and the remaining 19 were on the short side.

The average winning trade returned a profit of 0.425%. The average losing trade cost the account 1.701%.

Dan tested two different positions sizes for the strategy. His 5% Max Loss version traded 2 spread and his 10% Max Loss version traded 5 spreads. The 5% Max Loss version returned 10.19% for the year with a maximum drawdown of 15.68%. The 10% Max Loss version returned 25.48% for the year with a maximum drawdown of 35.41%.

The Equity Curves

The equity curves Dan provides do a great job of illustrating the steamroller point. Both versions of the strategy were cruising right along when they were suddenly smacked with severe losses in early April. Dan explains that there were actually two huge losses in a row that month.

In order to explain how severe those losses were, Dan provides the returns for the year if those two trades weren’t made. In that case, the 5% Max Loss version would have returned 20.81% for the year with a 5.82% maximm drawdown. The 10% Max Loss version would have returned 52.03% for the year with a 13.14% maximum drawdown. Those returns sound great, but they are just wishful thinking because those two big losses actually did happen.

Dan explains that the major flaw with strategies like this is that when things get bad, they do so in a hurry. It is also a concern that the very low point of the equity curve is exactly where most traders would give up on the strategy. If you started trading the 10% Max Loss version with $10,000 in January of 2013, after the two big losses in April you would be left with less than $8,000. Would you have the courage to keep trading?

The goal of every quantitative trader is to maximize the average profit per trade of their strategy. One way to increase the profitability of both winning and losing trades is through the process of pyramiding positions.

This concept, which was made popular by famous trader Jesse Livermore, allows your system to make a trade prove itself before you commit the entire position size. That way, if a trade is unprofitable from the start, you are not likely to lose as much as if you had entered the full position all at once.

While pyramiding positions is popular among stock traders, the concept is often overlooked by quantitative Forex traders.

An article that was posted by Chris Svorcik on Winner’s Edge Trading last week explored some of the pros and cons of scaling in and out of trades in this manner. The article also covered some of the different ways that this strategy could be implemented by Forex traders.

Different Ways To Pyramid Positions

The first portion of Svorcik’s article explains how pyramiding positions can open up quite a few more options for a given strategy. He explains that a strategy basically has three options: trade immediately, wait to trade on a pullback, or wait to trade on a breakout. Each of these options work better with some specific strategies than others.

What pyramiding does is allows those options to become what Svorcik calls a “trading decision tree.” This means that if your strategy uses a breakout as an entry signal, you can then have a second entry positions that is signaled by either a pullback or second breakout. This way of scaling into a position gives a trader plenty of flexibility to fine-tune a strategy.

Svorcik continues by explaining that the same options exist to scale out of positions. This could mean cutting a position in half as it loses ground, or it could mean taking some profits off the table as a position runs higher. This allows a strategy to implement multiple profit targets or stop-losses.

Svorcik also points out that pyramiding does not have to be used on both sides of a trade. It can be used exclusively for entries, or exclusively for exits if either option improves your strategy.

Pros & Cons of Pyramiding

Advantages

Obviously, the biggest positive associated with pyramiding in and out of positions is that your capital will be better protected. This can allow you to keep your losses smaller, while still getting capital into your winning trades.

Another advantage the Svorcik points out is that the use of pyramiding will introduce a new level of flexibility into your trading plan. This should enable it to better handle volatile and changing markets.

Adding a pyramiding component to your strategy will allow you to improve your potential profit overall, while at the same time limiting your overall risk.

Disadvantages

On the down side, Svorcik points out that pyramiding positions will make your strategy more complicated. That means it will likely require more of your time and attention.

Another negative aspect of pyramiding is that you will be incurring more transactions, which will drive up your implementation costs.

Finally, by pyramiding into winning positions and taking some profits off the table early, you will be costing yourself potential profit. You will have to backtest different pyramiding options to determine if the pros outweigh the cons in your particular situation.

I tend to be pretty paranoid about risk of ruin. That is why I almost always suggest adding some form of stop-loss protection to the systems I write about. It just makes sense to me that you should do everything possible to protect your trading capital.

Some of the strategies I have profiled seem to leave themselves open to holding large losing positions. My simple solution to this problem is always to add a simple stop-loss component. However, that could be detrimental to the overall performance of the system.

A recent guest post on System Trader Success forced me to take a deeper look at whether stops are actually worth using. The post was written by Rob Hanna from Quantifiable Edges.

Rob explains that he primarily trades mean reversion strategies similar to the ones that Larry Connors has published in his books. He explains that Connors has written about the tendency of stops to reduce overall performance. Rob has done his own research on the topic as well:

If the system suggests the security should bounce when it drops to $20 and it continues to $18, then it is REALLY overdue for a bounce. Any level of stop ensures you are selling an extremely oversold security that is making a low.

Those are buying conditions for oversold systems – not selling conditions.

The trend following crowd won’t agree with what Rob is saying about a security being “really overdue for a bounce,” but it will make sense to mean reversion traders. Rob also points out a stop strategy that seems to have the least negative impact on his oversold systems:

Wait until the security bounces for a bar or two. Look for a higher high, higher low, and higher close – or at least 2 of those 3.

Then place a stop under the swing low that was just made. In cases like this even if the security doesn’t hit your target exit price, it still ensures that you won’t have to suffer through the entire next leg down.

While it seems logical and can sometimes help avoid catastrophic trades in the long run, you’re normally better off just waiting for the mean reversion to occur and exiting at your target level.

He also makes the point that position sizing is extremely important and suggests using options to place trades instead of stops:

Not using stops does not equal not controlling risk. Position sizing becomes very important.

Traders could also consider using options to trade their short-term positions. Options provide a natural stop (zero).

Rob closes his piece by reminding us that he is specifically talking about mean reversion systems. He agrees that stops can be very effective when used with trend following systems.

The interesting take-away from this piece is that the type of strategy you are trading should be what influences your choice of stop-loss strategy more than your personal risk tolerance. If you are struggling with the risks your system takes, changing strategies might be a better option than adding stops.

Money management is such an important part of your trading system, I thought I would go over some other concerns. There is much more to proper money management than just picking a lot size. As a matter of fact, it is a synergistic relationship between many aspects of your trading system working together and your trading personality.

Here is what I mean…

These are some of the things that need to work together in order for your to have good money management:

Your stop loss size

Your take profit targets

Your win/loss ratio

Your risk/reward ratio

How many trades you take on an account

Your trading personality (More on this below)

All these things need to be working in alignment so you can safely grow your account. Money management is really RISK management and should be approached by focusing on the worst case scenario.

What would happen to my trading system during a losing streak?

I know, it is a lot more exciting to focus on how much money you can make. But if you are not prepared for an eventual losing streak, poor money management can quickly eat up your account. But if you only focus on preventing loss, you are going to end up sacrificing gains. And therein lies the problem.

You need to walk a tightrope with your money management so the gains fulfill your GREED and your losses don’t trigger your FEAR.

Are you watching the trading screen with fear in your eyes?

Money Management In Terms Of Greed And Fear

You’ve probably heard you need to keep emotions like greed and fear out of your trading. Unfortunately, I think this is impossible. In reality, you need to learn to live with the emotions of greed and fear, and that has a lot to do with aligning your money management with your trading personality.

Fulfillment Of Greed

Let’s say you have a $10,000 account and only want to trade 0.01 lots per trade with a 50 pip stop loss and 75 pip take profit. This is a very conservative money management strategy. Yes, you would not be risking too much on your trades, but would you be satisfied with the gains? Would you be able to trade like this long term and fulfill your trading goals?

In the end, you need a money management strategy in place that has the potential to fulfill your trading and financial goals. Otherwise, you are not going to feel satisfied with the efforts you put into your trading. This can lead to abandoning trading all together, or implementing risky trading practices to look for the profits you are missing.

Avoidance Of Fear

So, you want a money management strategy that can fulfill your economic goals, but you don’t want to be kept up at night. Any time you place a trade and put real money at risk there is a certain amount of excitement. (Even if you are using an expert advisor to place and manage your trades, you still are emotionally invested in the trading when you look at your account and the results).

However, every trade you place can not be “do-or-die”. Trading is a long term activity and you’ll never last if you are overstressed by each trade you place. You need to be able to handle the trading emotionally by not risking too much on any one trade. Essentially, you need to find a level of fear you can live with.

As you can see, the money management strategy you use is a compromise between wanting to make as much money as possible and not putting your money unnecessarily at risk to the point you cannot sleep at night.

Every trader is different. There is not ONE money management strategy that is right for everyone. This is a personal choice you will have to make for yourselves.

I will say this though…

In my experience with would-be traders, I find most people tend to set their trading goals extremely high. They are either looking for an extremely high win rate, or the ability to make large percentage gains each month on a consistent basis. These goals usually lead to using risky trading and money management techniques.

In order to align your money management with your trading personality, you need to first take a look at your trading personality. Are your goals realistic and achievable?

In most cases, I think it is necessary to lower your expectations for trading and work on using a money management strategy to achieve these lowered goals. (You’d be surprised how much following this one bit of advice can increase your chances of trading success).

In keeping with the money management theme, I want to talk next time about win/loss ratio versus risk/reward ratio. In the meantime, leave comments about money management in terms of greed and fear. Have you ever thought of money management in these terms before?

Most methods for placing stops are based on either money management principles or technical analysis. Using Bayesian Inference is an alternative solution that lets you update your stops periodically to account for new price data. This assures that you always have a mathematically optimal stop set.

How Bayesian Stops Work

Bayesian Inference allows you to make a prediction about an uncertain future event and then adjust the probability of that prediction happening as more data is introduced. Applied to trading, Bayesian Inference allow us to project an expected positive outcome of a position as we establish it, and then adjust our expectations as time passes and more price data is introduced.

In a perfect world, every position we establish would move in a straight line from our entry point to our target profit point, increasing the same amount each day. Obviously, this doesn’t happen.

If we break down that ideal daily increase, we can use Bayesian Inference to determine the probability of getting to our original target based on where a position actually is relative to its ideal position. We can use that information to mathematically determine when our position has strayed too far from its expected path.

How Bayesian Stops Are Calculated

The first step in calculating where to place your Bayesian stops is to determine your initial position, target price, and expected time frame.

As a system trader, I don’t like the idea of forecasting prices. In order to apply this idea to system trading, I replaced the idea of “forecasting” with “projecting backtesting results.” This means that we are using fact based, tested numbers for our projections, not pulling numbers out of the clouds.

Once we have those numbers, we can calculate our ideal path with respect to whatever timeframe we are trading. This is done by dividing the projected profit by the time frame. We will also need to estimate the price range that will compose the middle 50% of our prior probability bell curve.

After the first time period passes and we receive our first data point, we can plug that into our Bayesian probability formula to calculate the mean of the posterior probability distribution.

While breaking down this formula in depth can be an enjoyable way to spent a weekend for a stats nerd like myself, you could also google “bayesian stop excel spreadsheet” and download a spreadsheet that will do all of the complicated math for you.

When all of the complex math is behind us, we just need to make sure that the mean of the posterior probability distribution stays above the ideal path that we projected. Our stop is the point where the mean posterior probability distribution drops below the ideal path. At that point, our trade is mathematically too far removed from the projected path to recover.

Example Using The 10/100 SPY System

The system last gave a buy signal on December 7, 2012. The price on that day (adjusted) was 140.78.

Backtesting results have shown that the 10/100 system has an average profit of 3.2% and an average trade length of 12 weeks. Using that data, we can expect the system to increase 4.51 over 12 weeks, or .38 / week.

By pulling the historic price data, we can put together the following chart:

A spreadsheet helps to calculate the Bayesian probabilities

As you can see, in each of the first four weeks of this trade, the mean of the posterior distribution was higher than the ideal path we projected. This held true even after the third week when the position was showing a loss. As we all know, this trade ended up being extremely successful.

Advantages & Disadvantages For System Traders

As you can see, using Bayesian Inference to set stops could be very beneficial to a systems trader. It gives us the ability to take the results of our historical backtesting and project those results forward.

It also gives us the ability to establish trailing stops that will always be adjusted to the mathematically optimal position based on what the market is actually doing.

On the other hand, this method implements some extremely complicated statistical analysis. This goes against the simplicity that is the root of most trading system approaches.

There is also a strong possibility that anyone implementing this method will not give enough respect to the fat tail, or black swan, events that actually happen far more often than a standard distribution says they should. Therefore, this could end up being an overly risky method.

So far in this series about building a solid trading system we’ve identified the mechanics of your trading system. By that I mean… when you are going to trade, what time frame to trade, when to get into the market, where to put your initial stop loss and take profit and how you are going to manage the trade after it is placed. Now it is time to talk a little about the most important part of any trading system… money management.

Your money management strategy can mean the difference between success and failure.

If I gave the exact same trading system rules (without money management), to two different traders, each trader would get very different results. It is possible for one trader to be extremely profitable while the other blows out their account. The difference is the money management strategy they use. This is why money management is the most important aspect of your trading system.

Money management is basically RISK management. A novice way of looking at trading is to focus on how much money you can make. A more professional approach is to focus on how much money you can lose. In my opinion, it is best to lower your earning expectations and focus on losing less money.

So, how much money do your risk on each trade? At the end of the day, you need to figure out the lot size you are going to use when you get into the markets. There is a lot to consider when making this decision.

Money Management Considerations

Your Account Balance:

Traders seem to take a different approach to money management depending on the size of their trading account. Traders with small accounts tend to be aggressive, and traders with large accounts tend to be conservative. (My advice is to adopt a money management strategy you would feel comfortable trading on a large account, regardless of your starting account size).

The Stop Loss Size:

Your stop loss determines the number of pips you are willing to risk on the trade. This value is used to determine what lot size you can use per pip that fits with your risk strategy. For example, if you only want to risk $200 and use a 20 pip stop, each pip can have the value of $10.

The Take Profit Size:

The relationship between what you are willing to risk to what you hope to gain is your risk to reward ratio. A good overall strategy needs to take these two values in consideration (stop loss size and take profit size), to ensure a positive starting risk to reward.

How Many Trades You Place At One Time:

If you are taking more than one trade at a time, this needs to be factored into your overall strategy. You need to figure out the money management for each trade while taking the maximum number of trades that can be placed at one time. For example, if you want to use 2% of your balance per trade and take 5 trades at a time… you really are risking 10% of your account at any one time.

Currency Pair:

Different currency pairs have different pip values. It is not always the case where 0.01 lots equals $0.10, 0.1 lots equals $1 and 1.0 lots equals $10.

Your Risk Tolerance:

Obviously, this is a personal choice. Some people can handle more risk than others. You need to align your money management strategy with your trading personality. Only a good fit between your risk management and your personality will stand the test of time.

4 Common Money Management Strategies

Here are 4 pretty straight forward risk management strategies…

Fixed Lots:

You simply decide on a fixed lot size for each trade, like 0.02 lots per trade. While this is the simplest of all methods, it does have its problems. For example, depending on the stop loss size used, the risk is different per trade. (A trade with a 20 pip stop loss risks substantially less than a trade with a 80 pip stop loss).

If you were to use use Fixed Lots, it is a good idea to use a very conservative setting. If you use too high a lot size, you can easily get into trouble when you hit a losing streak.

Fixed Dollar Amount:

You could determine a dollar amount you feel comfortable risking for each trade. For example you could risk $100 per trade, if your account balance permitted. Depending on the stop loss size, you would have to figure out the lot size that corresponds to $100.

This method helps emotionally. If you choose a dollar amount that does not produce too much stress, each trade is the same in terms of potential loss. One trade does not take on more importance than another.

X Lots Per Y Balance:

You could decide to use a certain lot size per dollar amount in your account. For example, you could say you want to use 0.01 lots per $1000 in your account. In this way, the lots size increases as your account balance increases. When your account reaches $2000, you would start trading 0.02 lots.

You need to take into account your starting balance, typical stop loss sizes, how many trades you take at one time, etc. to make sure you are not risking too much of your account at any one time. Don’t jump into using a strategy like this without taking into account the worst case scenario… where you loss every trade placed on any given day, or hit a losing streak.

Fixed Percentage Per Trade:

This is where you decide on a percentage per trade you are willing to risk. For example, you could say you want to risk 2% per trade. You take 2% of your account balance and divide it by your stop loss to figure out the lot size per pip you can use per trade.

This approach is popular with pro traders because each trade has the same value proportionally, independent of the stop loss used. A trade with a stop loss of 20 pips is the same as a trade with 200 pips in terms of percentage of account at risk. Plus as your balance increases, so does your lot sizes and potential profits.

Money management is a big topic, and this is getting long. I think I’m going to have to do another post to touch on other aspects and the importance of this topic. I know trading strategy entries are more exciting, but it is the “boring” topic of money management that can mean all the difference to your trading system’s success.

If you have a favorite money management strategy or something to add, please leave a comment and share it. What money management strategy works best with your trading personality?